Transmission Line-Planning Method Based on Adaptive Resolution Grid and Improved Dijkstra Algorithm

Abstract

An improved Dijkstra algorithm based on adaptive resolution grid (ARG) is proposed to assist manual transmission line planning, shorten the construction period and achieve lower cost and higher efficiency of line selection. Firstly, the semantic segmentation network is used to change the remote sensing image into a ground object-identification image and the grayscale image of the ground object-identification image is rasterized. The ARG map model is introduced to greatly reduce the number of redundant grids, which can effectively reduce the time required to traverse the grids. Then, the Dijkstra algorithm is combined with the ARG and the neighborhood structure of the grid is a multi-center neighborhood. An improved method of bidirectional search mechanism based on ARG and inflection point-correction is adopted to greatly increase the running speed. The inflection point-correction reduces the number of inflection points and reduces the cost. Finally, according to the results of the search, the lowest-cost transmission line is determined. The experimental results show that this method aids manual planning by providing a route for reference, improving planning efficiency while shortening the duration, and reducing the time spent on algorithm debugging. Compared with the comparison algorithm, this method is faster in running speed and better in cost saving and has a broader application prospect.

A Semantic Segmentation Method Based on AS-Unet++ for Power Remote Sensing of Images

“…Based on geographic information, such as houses, roads, forests, rivers, etc., selection algorithms can plan a reasonable transmission line. Hence, accurate geographic information is essential for the automatic construction of transmission lines [ 1 , 2 ]. With the progress of satellite technology, the image resolution acquired by remote sensing satellites is constantly improving.…”